Mixed Exponentially Weighted Moving Average—Moving Average Control Chart with Application to Combined Cycle Power Plant

Muhammad Ali Raza, Komal Iqbal, Muhammad Aslam (), Tahir Nawaz, Sajjad Haider Bhatti and Gideon Mensah Engmann
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Muhammad Ali Raza: Department of Statistics, Government College University Faisalabad, Faisalabad 38000, Pakistan
Komal Iqbal: Department of Statistics, Government College University Faisalabad, Faisalabad 38000, Pakistan
Muhammad Aslam: Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah 21551, Saudi Arabia
Tahir Nawaz: Department of Statistics, Government College University Faisalabad, Faisalabad 38000, Pakistan
Sajjad Haider Bhatti: College of Statistical Sciences, University of the Punjab, Lahore 54590, Pakistan
Gideon Mensah Engmann: Department of Biometry, C. K. Tedam University of Technology and Applied Sciences, Navrongo P.O. Box 24, Ghana

Sustainability, 2023, vol. 15, issue 4, 1-17

Abstract: Statistical process control (SPC) consists of various tools for effective monitoring of the production processes and services to ensure their stable and satisfactory performance. A control chart is an important tool of SPC for detecting the process shifts that may undermine the quality of the products or services. In the literature, a mixed exponentially weighted moving average–moving average (EWMA–MA) control chart for monitoring the process location is proposed to enhance the overall shift detection ability of the EWMA control chart. It is noted that the moving averages terms were considered as independent irrespective of their order. Consequently, the covariance terms are ignored while deriving the variance expression of the monitoring statistic. However, the successive moving averages of span w might not be independent since each term includes w − 1 preceding samples’ information. In this study, the variance expression of the mixed EWMA-MA charting statistic is derived by considering the dependency among the sequential moving averages. The control limits of the mixed EWMA-MA control chart are revised and the run-length profile is studied by using Monte Carlo simulations. The performance of the mixed EWMA-MA chart is compared with the existing counterparts and its robustness under various process distributions is studied. In the end, a real-life example is provided to demonstrate its application by using the data from a combined cycle power plant.

Keywords: average run length; control chart; exponentially weighted moving average; moving average; Monte Carlo simulation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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